Abstract: The recent technological progress contributes to a huge increase of 3D models available in digital forms.
Numerous applications were developed to deal with this amount of information, especially for 3D shape
retrieval. One of the main issues is to break the semantic gap between shapes desired by users and shapes
returned by retrieval methods. In this paper, we propose an algorithm to address this issue. First the user gives
a semantic request. Second, a fuzzy 3D-shape generator sketches out suitable 3D-shapes. Those shapes are
filtered by the user or a learning machine to select the ones that match the semantic query. Then, we use a
state-of-the-art retrieval method to return real-world 3D shapes that match this semantic query. This algorithm
is used to retrieve object in SHREC’07 database. The results are good and promising.